A Statistical Physics Perspective to Understand Social Visual Attention in Autism Spectrum Disorder

Are there jumps in evidence accumulation, and what, if anything, do they reflect psychologically? An analysis of Lévy Flights models of decision-making

According to existing theories of simple decision-making, decisions are initiated by continuously sampling and accumulating perceptual evidence until a threshold value has been reached. Many models, such as the diffusion decision model, assume a noisy accumulation process, described mathematically as a stochastic Wiener process with Gaussian distributed noise. Recently, an alternative account of decision-making has been proposed in the Lévy Flights (LF) model, in which accumulation noise is characterized by a heavy-tailed power-law distribution, controlled by a parameter, [Formula: see text]. The LF model produces sudden large "jumps" in evidence accumulation that are not produced by the standard Wiener diffusion model, which some have argued provide better fits to data. It remains unclear, however, whether jumps in evidence accumulation have any real psychological meaning. Here, we investigate the conjecture by Voss et al. (Psychonomic Bulletin & Review, 26(3), 813-832, 2019) that jumps might reflect sudden shifts in the source of evidence people rely on to make decisions. We reason that if jumps are psychologically real, we should observe systematic reductions in jumps as people become more practiced with a task (i.e., as people converge on a stable decision strategy with experience). We fitted five versions of the LF model to behavioral data from a study by Evans and Brown (Psychonomic Bulletin & Review, 24(2), 597-606, 2017), using a five-layer deep inference neural network for parameter estimation. The analysis revealed systematic reductions in jumps as a function of practice, such that the LF model more closely approximated the standard Wiener model over time. This trend could not be attributed to other sources of parameter variability, speaking against the possibility of trade-offs with other model parameters. Our analysis suggests that jumps in the LF model might be capturing strategy instability exhibited by relatively inexperienced observers early on in task performance. We conclude that further investigation of a potential psychological interpretation of jumps in evidence accumulation is warranted.

Effects of Physical Exercise and Virtual Training on Visual Attention Levels in Children with Autism Spectrum Disorders

This study compared the effects of physical exercise (PE) and virtual training (VT) on the improvement of the visual attention mechanism in children with autism spectrum disorders (ASD). One hundred eighty-nine children with ASD were recruited from Orphan School in Liaoning Province, China. After screening, 100 children ultimately participated in the experiment. Children with ASD were randomly assigned to VT (VT, n = 34), PE (PE, n = 33) and control group (CG, n = 33). The VT group experiment was performed in a virtual environment through the game FIFA21 three times per week for 6 weeks. The PE group played physical football matches three times per week for 6 weeks. Children with ASD in the CG group did not receive VT or PE but only received psychological counseling. Visual attention of children with ASD is evaluated by using the multiple object tracking paradigm (MOT). After 6 weeks of observation, although none of the three groups saw improvements in the correct rate of ring tracking, the observations of the VT and PE groups were significant (p < 0.05) compared to the CG group in finding detection rate of probe stimulus. Through MOT tests, VT and PE improved the detection rate of probe stimulus in children with ASD. Therefore, this paper indicates that VT and PE can improve the visual attention ability of children with ASD.

Computer-Aided Screening of Autism Spectrum Disorder: Eye-Tracking Study Using Data Visualization and Deep Learning

Background

The early diagnosis of autism spectrum disorder (ASD) is highly desirable but remains a challenging task, which requires a set of cognitive tests and hours of clinical examinations. In addition, variations of such symptoms exist, which can make the identification of ASD even more difficult. Although diagnosis tests are largely developed by experts, they are still subject to human bias. In this respect, computer-assisted technologies can play a key role in supporting the screening process.

Objective

This paper follows on the path of using eye tracking as an integrated part of screening assessment in ASD based on the characteristic elements of the eye gaze. This study adds to the mounting efforts in using eye tracking technology to support the process of ASD screening

Methods

The proposed approach basically aims to integrate eye tracking with visualization and machine learning. A group of 59 school-aged participants took part in the study. The participants were invited to watch a set of age-appropriate photographs and videos related to social cognition. Initially, eye-tracking scanpaths were transformed into a visual representation as a set of images. Subsequently, a convolutional neural network was trained to perform the image classification task.

Results

The experimental results demonstrated that the visual representation could simplify the diagnostic task and also attained high accuracy. Specifically, the convolutional neural network model could achieve a promising classification accuracy. This largely suggests that visualizations could successfully encode the information of gaze motion and its underlying dynamics. Further, we explored possible correlations between the autism severity and the dynamics of eye movement based on the maximal information coefficient. The findings primarily show that the combination of eye tracking, visualization, and machine learning have strong potential in developing an objective tool to assist in the screening of ASD.

Conclusions

Broadly speaking, the approach we propose could be transferable to screening for other disorders, particularly neurodevelopmental disorders.

Attentional Cueing and Executive Deficits Revealed by a Virtual Supermarket Task Coupled With Eye-Tracking in Autism Spectrum Disorder

Executive functioning (EF) impairments in Autism Spectrum Disorder (ASD) impact on complex functions, such as social cognition. We assessed this link between EF, attentional cueing, and social cognition with a novel ecological task, "EcoSupermarketX." Our task had three blocks of increasing executive load and incorporated social and non-social cues, with different degrees of saliency. Performance of ASD and typical neurodevelopment was compared. The ASD showed a significant performance dependence on the presence of contextual cues. Difficulties increased as a function of cognitive load. Between-group differences were found both for social and non-social salient cues. Eye-tracking measures showed significantly larger fixation time of more salient social cues in ASD. In sum, EcoSupermarketX is sensitive to detect EF and attentional cueing deficits in ASD.

Visual preference for social vs. non-social images in young children with autism spectrum disorders. An eye tracking study

Autism Spectrum Disorders (ASD) are associated to social attention (SA) impairments. A gaze bias to non-social objects over faces has been proposed as an early marker of ASD. This bias may be related to the concomitant circumscribed interests (CI), which question the role of competing objects in this atypical visual behavior. The aim of this study was to compare visual attention patterns to social and non-social images in young children with ASD and matched typical controls (N = 36; age range 41-73 months) assessing the role of emotion in facial stimuli and the type of competing object. A paired preference task was designed pairing happy, angry, and neutral faces with two types of objects (related or not related to autism CI). Eye tracking data were collected, and three indexes were considered as dependent variables: prioritization (attentional orientation), preference, and duration (sustained attention). Results showed that both groups had similar visual pattern to faces (prioritization, more attention and longer visits to faces paired with objects non-related to their CI); however, the ASD group attended to faces significantly less than controls. Children with ASD showed an emotional bias (late orientation to angry faces and typical preference for happy faces). Finally, objects related to their CI captured attention in both groups, significantly reducing SA in children with ASD. Atypical SA is present in young children with ASD regardless the competing non-social object. Identifying strengths and difficulties in SA in this population may have substantial repercussion for early diagnosis, intervention, and ultimately prognosis.

Visual Exploration of Dynamic or Static Joint Attention Bids in Children With Autism Syndrome Disorder

Eye-tracking studies have revealed a specific visual exploration style characterizing individuals with autism spectrum disorder (ASD). The aim of this study is to investigate the impact of stimulus type (static vs. dynamic) on visual exploration in children with ASD. Twenty-eight children with ASD, 28 children matched for developmental communication age, and 28 children matched for chronological age watched a video and a series of photos involving the same joint attention scene. For each stimulus, areas of interest (AOI) were determined based on Voronoi diagrams, which were defined around participants' fixation densities, defined by the mean shift algorithm. To analyze the eye-tracking data on visual exploration, we used a method for creating AOI a posteriori, based on participants' actual fixations. The results showed the value of both kinds of stimuli. The photos allowed for the identification of more precise AOI and showed similarities in exploration between ASD and typical children. On the other hand, video revealed that, among ASD children only, there are few differences in the way they look at the target depending on the deictic cue used. This raises questions regarding their understanding of a joint attention bid recorded on a video. Finally, whatever the stimulus, pointing seems to be the most important element for children looking at the target.

Spatiotemporal characteristics of gaze of children with autism spectrum disorders while looking at classroom scenes

Children with autism spectrum disorders (ASD) who have neurodevelopmental impairments in social communication often refuse to go to school because of difficulties in learning in class. The exact cause of maladaptation to school in such children is unknown. We hypothesized that these children have difficulty in paying attention to objects at which teachers are pointing. We performed gaze behavior analysis of children with ASD to understand their difficulties in the classroom. The subjects were 26 children with ASD (19 boys and 7 girls; mean age, 8.6 years) and 27 age-matched children with typical development (TD) (14 boys and 13 girls; mean age, 8.2 years). We measured eye movements of the children while they performed free viewing of two movies depicting actual classes: a Japanese class in which a teacher pointed at cartoon characters and an arithmetic class in which the teacher pointed at geometric figures. In the analysis, we defined the regions of interest (ROIs) as the teacher's face and finger, the cartoon characters and geometric figures at which the teacher pointed, and the classroom wall that contained no objects. We then compared total gaze time for each ROI between the children with ASD and TD by two-way ANOVA. Children with ASD spent less gaze time on the cartoon characters pointed at by the teacher; they spent more gaze time on the wall in both classroom scenes. We could differentiate children with ASD from those with TD almost perfectly by the proportion of total gaze time that children with ASD spent looking at the wall. These results suggest that children with ASD do not follow the teacher's instructions in class and persist in gazing at inappropriate visual areas such as walls. Thus, they may have difficulties in understanding content in class, leading to maladaptation to school.